code: def prepare_input() -> torch.Tensor:
      aug = T.ResizeShortestEdge([800, 800], 1333)
      im: NDArray[np.float32] = np.asarray(
          Image.open(requests.get(url, stream=True).raw).convert("RGB")
      )
      arr: NDArray[np.float32] = aug.get_transform(im).apply_image(im)
      # NOTE: it is fine to copy here
      return torch.as_tensor(arr.transpose(2, 0, 1))
  
file_path: BentoML/tests/integration/frameworks/models/detectron.py
imports: from __future__ import annotations
  import typing
  import detectron2.config
  import detectron2.engine
  import detectron2.model_zoo
  import detectron2.modeling
  import numpy
  import requests
  import torch
  from detectron2.data import transforms
  from PIL import Image
  import bentoml
  from .None import FrameworkTestModel
  from .None import FrameworkTestModelConfiguration
  from .None import FrameworkTestModelInput
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_input() and returns: torch